This PMLE practice question tests your understanding of pmle exam topics. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Network Topology
A team trains a distributed TensorFlow model using the config above. After training, they deploy the model for online predictions. The model returns poor quality predictions. They suspect that the model was not trained correctly due to a configuration error. What is the most likely mistake?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Network Topology
A
The `scaleTier` is set to 'STANDARD_1' which only supports up to 3 workers.
STANDARD_1 limits workers to 3; the actual job may have ignored the 10 worker setting.
B
The training job is using a custom container that does not match the requirements.
Why wrong: There is no indication of a custom container; the config uses package_uris.
C
The model was exported incorrectly because the training job did not specify a `--model-export-path`.
Why wrong: The model-dir argument is used; export path is fine.
D
The parameter server count should be at least equal to the worker count.
Why wrong: No such requirement; parameter servers can be fewer.
The answer is that the `scaleTier` set to 'STANDARD_1' is the most likely mistake because this tier caps the distributed training cluster at a maximum of three workers, yet the configuration specifies ten workers. When a Distributed TensorFlow scale tier configuration error occurs, the extra worker requests are silently ignored or cause the job to fall back to a smaller cluster, meaning the model trains with far fewer resources than intended. This directly leads to under-trained parameters and poor prediction quality upon deployment. On the Google Professional Machine Learning Engineer exam, this scenario tests your understanding of how `scaleTier` values map to actual cluster topology in AI Platform Training, a common trap being that candidates assume all workers are honored regardless of tier. A useful memory tip is to think of the tier name as a hard limit: "STANDARD_1" equals one plus two, not ten.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The `scaleTier` is set to 'STANDARD_1' which only supports up to 3 workers.
The correct answer is A. The `scaleTier` set to 'STANDARD_1' only supports a maximum of 3 workers, but the configuration specifies 10 workers. This mismatch causes the training job to either ignore the worker count and run with fewer workers or fail to allocate the intended resources, leading to an undertrained model and poor predictions. Option B is incorrect because the use of a custom container is not inherently problematic. Option C is incorrect because a `--model-export-path` is not required; the model directory is specified separately. Option D is incorrect because the parameter server count does not need to equal the worker count; it can be smaller.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
The `scaleTier` is set to 'STANDARD_1' which only supports up to 3 workers.
Why this is correct
STANDARD_1 limits workers to 3; the actual job may have ignored the 10 worker setting.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The training job is using a custom container that does not match the requirements.
Why it's wrong here
There is no indication of a custom container; the config uses package_uris.
✗
The model was exported incorrectly because the training job did not specify a `--model-export-path`.
Why it's wrong here
The model-dir argument is used; export path is fine.
✗
The parameter server count should be at least equal to the worker count.
Why it's wrong here
No such requirement; parameter servers can be fewer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which PMLE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: The `scaleTier` is set to 'STANDARD_1' which only supports up to 3 workers. — The correct answer is A. The `scaleTier` set to 'STANDARD_1' only supports a maximum of 3 workers, but the configuration specifies 10 workers. This mismatch causes the training job to either ignore the worker count and run with fewer workers or fail to allocate the intended resources, leading to an undertrained model and poor predictions. Option B is incorrect because the use of a custom container is not inherently problematic. Option C is incorrect because a `--model-export-path` is not required; the model directory is specified separately. Option D is incorrect because the parameter server count does not need to equal the worker count; it can be smaller.
What should I do if I get this PMLE question wrong?
Identify which PMLE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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